Hi Matthew,
I've been working on "rolling/windowed" libraries for quite a while.
I'm currently working on implementations for basic moment and rank
statistics - they are pretty much done and I am trying to maneuver them
into apache commons math for java.
I am also interested in implementing these statistics for python/numpy and
R. I have seen a little bit for R, but nothing yet for numpy.
/brad
On Nov 25, 2007 5:00 PM, Matthew Perry <perrygeo@gmail.com> wrote:
> Hi all,
>> I'm not sure if my terminology is familiar but I'm trying to do a
> "moving window" analysis (ie a spatial filter or kernel) on a 2-D
> array representing elevation. For example, a 3x3 window centered on
> each cell is used to calculate the derivate slope of that cell.
>> Can this easily be implemented using numpy?
>> Currently I have tried implementing in pure python loops (too slow)
> and c++ (fast but more difficult to compile, distribute, wrap in
> python calls, etc). I think a good solution would be to leverage numpy
> which is both fast and and easy package for end users to install.
>> An example of the C++ code I'm trying to emulate is at
>http://perrygeo.net/download/hillshade.html . Does anyone have any
> tips or examples out there? Where should I start researching this?
>> --
> Matthew T. Perry
>http://www.perrygeo.net> _______________________________________________
> Numpy-discussion mailing list
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